云服务资源安全服务质量的不透明性已成为阻碍云服务快速发展的瓶颈性问题，保障客户权益、增强云服务资源透明性等问题的解决亟需研究和构建一种有效和可靠的云服务安全质量问责机制。本项目针对面向云服务的异质服务资源空间结构描述和基于云服务网络的SLA合规性问题判定与归属两个科学问题展开。基于复杂网络理论、时间自动机模型等的云服务网络空间结构研究，构建复杂异质云服务资源网络模型以及研究建立面向动态云服务网络时序生成模型；并基于上述模型，研究基于安全SLA的云服务合规性判定技术和云服务网多源责任节点溯源技术，形成一个集“建网-判定-溯源”为一体的复杂时序云服务网络异质服务资源的问责机制框架，提高云服务异质服务资源的安全责任判定能力及责任节点溯源能力，增加云服务资源的安全透明性，为建立自主有效的面向云服务安全领域的问责机制提供有力的理论和技术支持，能为我国未来云计算的可靠服务及服务优化提供有效的支撑。

The opacity of cloud service resource security QoS has become a bottleneck for the rapid development of cloud services, The accountability about safety and quality of cloud service is an important measure to protect the rights and interests of customers， and also promote the quality of cloud services. The accountability mechanism of cloud service is an important content of cloud service security. This project focuses on two scientific problems, which are the spatial structure description of heterogeneous service resources for cloud services, verifying and tracing SLA compliance problem based on cloud service network. Based on the complex network theory and time automata model, this project presents the basic model of cloud service behavior model, security SLA model and cloud service network, in order to construct complex heterogeneous cloud service resource network model, and establish dynamic timing generation cloud service Network model. From the above theoretical model, this project gives the cloud service compliance decision technology based on secure SLA, breaks the difficulty of traceability of multi-source node in cloud service network, and finally forms an accountability mechanism framework involves "modeling - judgment - traceability" of the heterogeneous cloud service network,improve the ability to determine the security responsibility of heterogeneous cloud service resources and to trace the source of the responsibility node, and increase the security transparency of cloud service resources.The research and development of our project is objective to provide powerful theory and technical support in the field of cloud safety problem, and also provide effective support for our future research on reliable services and service optimization of cloud computing.